1 citations · 3 across the 9 of their papers we have counts for
10 papers
UltraDub: Towards Authentic Dubbing by Unifying Visually-Steered Flow Learning and Trajectory Guidance
Gaoxiang Cong, Liang Li, Jianwei Wen +3
Visual voice cloning requires intelligible, speaker-consistent speech synchronized with visible articulation. However, sequential multimodal conditioning can disrupt previously est…
Hierarchical Codec Diffusion for Video-to-Speech Generation
Jiaxin Ye, Gaoxiang Cong, Chenhui Wang +4
Video-to-Speech (VTS) generation aims to synthesize speech from a silent video without auditory signals. However, existing VTS methods disregard the hierarchical nature of speech,…
CoSyncDiT: Cognitive Synchronous Diffusion Transformer for Movie Dubbing
Gaoxiang Cong, Liang Li, Jiaxin Ye +4
Movie dubbing aims to synthesize speech that preserves the vocal identity of a reference audio while synchronizing with the lip movements in a target video. Existing methods fail t…
STaR: Sensitive Trajectory Regulation for Unlearning in Large Reasoning Models
Jingjing Zhou, Gaoxiang Cong, Li Su +1
Large Reasoning Models (LRMs) have advanced automated multi-step reasoning, but their ability to generate complex Chain-of-Thought (CoT) trajectories introduces severe privacy risk…
InstructDubber: Instruction-based Alignment for Zero-shot Movie Dubbing
Zhedong Zhang, Liang Li, Gaoxiang Cong +5
Movie dubbing seeks to synthesize speech from a given script using a specific voice, while ensuring accurate lip synchronization and emotion-prosody alignment with the character's…
FlowDubber: Movie Dubbing with LLM-based Semantic-aware Learning and Flow Matching based Voice Enhancing
Gaoxiang Cong, Liang Li, Jiadong Pan +5
Movie Dubbing aims to convert scripts into speeches that align with the given movie clip in both temporal and emotional aspects while preserving the vocal timbre of a given brief r…
Towards Expressive Video Dubbing with Multiscale Multimodal Context Interaction
Yuan Zhao, Rui Liu, Gaoxiang Cong
Automatic Video Dubbing (AVD) generates speech aligned with lip motion and facial emotion from scripts. Recent research focuses on modeling multimodal context to enhance prosody ex…
EmoDubber: Towards High Quality and Emotion Controllable Movie Dubbing
Gaoxiang Cong, Jiadong Pan, Liang Li +5
Given a piece of text, a video clip, and a reference audio, the movie dubbing task aims to generate speech that aligns with the video while cloning the desired voice. The existing…
StyleDubber: Towards Multi-Scale Style Learning for Movie Dubbing
Gaoxiang Cong, Yuankai Qi, Liang Li +6
Given a script, the challenge in Movie Dubbing (Visual Voice Cloning, V2C) is to generate speech that aligns well with the video in both time and emotion, based on the tone of a re…
Learning to Dub Movies via Hierarchical Prosody Models
Gaoxiang Cong, Liang Li, Yuankai Qi +6
Given a piece of text, a video clip and a reference audio, the movie dubbing (also known as visual voice clone V2C) task aims to generate speeches that match the speaker's emotion…